Package edu.cmu.tetrad.search.test

Class IndTestConditionalGaussianLrt

java.lang.Object

edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt

All Implemented Interfaces:

IndependenceTest

public class IndTestConditionalGaussianLrt
extends Object
implements IndependenceTest

Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete. This test is valid for both ordinal and non-ordinal discrete searchVariables.

Assumes a conditional Gaussain model and uses a likelihood ratio test.

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
IndTestConditionalGaussianLrt(DataSet data, double alpha, boolean discretize)	Consstructor.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, List<Node> z)	Returns and independence result that states whetehr x _||_y | z and what the p-value of the test is.
boolean	determines(List<Node> z, Node y)	Returns true if y is determined the variable in z.
double	getAlpha()	Returns the significance level of the independence test.
DataSet	getData()	Returns the data.
double	getPValue()	Returns the probability associated with the most recently executed independence test, or Double.NaN if p value is not meaningful for this test.
double	getScore()	Returns a number that is higher for stronger judgments of dependence and negative for judgments of independence.
List<Node>	getVariables()	Returns the list of variables over which this independence checker is capable of determining independence relations.
IndependenceTest	indTestSubset(List<Node> vars)	Returns an Independence test for a sublist of the variables.
boolean	isVerbose()	Returns true iff verbose output should be printed.
void	setAlpha(double alpha)	Sets the significance level.
void	setNumCategoriesToDiscretize(int numCategoriesToDiscretize)	Sets the nubmer of categories used to discretize variables.
void	setVerbose(boolean verbose)	Sets whether verbose output should be printed.
String	toString()	Returns a string representation of this test.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface edu.cmu.tetrad.search.test.IndependenceTest

checkIndependence, getCov, getDataSets, getSampleSize, getVariable, getVariableNames

Constructor Details

IndTestConditionalGaussianLrt

public IndTestConditionalGaussianLrt(DataSet data,
 double alpha,
 boolean discretize)

Consstructor.

Parameters:

data - The data to analyze.

alpha - The signifcance level.

discretize - Whether discrete children of continuous parents should be discretized.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Description copied from interface: IndependenceTest

Returns an Independence test for a sublist of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Throws:

javax.help.UnsupportedOperationException - Method not implemented

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 List<Node> z)

Returns and independence result that states whetehr x _||_y | z and what the p-value of the test is.

Specified by:

checkIndependence in interface IndependenceTest

Returns:

an independence result (see)

See Also:

• IndependenceResult

getPValue

public double getPValue()

Returns the probability associated with the most recently executed independence test, or Double.NaN if p value is not meaningful for this test.

getVariables

public List<Node> getVariables()

Returns the list of variables over which this independence checker is capable of determining independence relations.

Specified by:

getVariables in interface IndependenceTest

Returns:

This list.

determines

public boolean determines(List<Node> z,
 Node y)

Returns true if y is determined the variable in z.

Specified by:

determines in interface IndependenceTest

Returns:

True if so.

getAlpha

public double getAlpha()

Returns the significance level of the independence test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

This level.

setAlpha

public void setAlpha(double alpha)

Sets the significance level.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - This level.

getData

public DataSet getData()

Returns the data.

Specified by:

getData in interface IndependenceTest

Returns:

This data.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

getScore

public double getScore()

Returns a number that is higher for stronger judgments of dependence and negative for judgments of independence.

Specified by:

getScore in interface IndependenceTest

Returns:

This number.

toString

public String toString()

Returns a string representation of this test.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

This string.

isVerbose

public boolean isVerbose()

Returns true iff verbose output should be printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

This.

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True if so.

setNumCategoriesToDiscretize

public void setNumCategoriesToDiscretize(int numCategoriesToDiscretize)

Sets the nubmer of categories used to discretize variables.

Parameters:

numCategoriesToDiscretize - This number, by default 3.